The objective of this project is to significantly improve our understanding of the heterogeneity of Alzheimer?s disease (AD) and common genetic mechanisms in aging and AD, and find new genetic targets for AD prevention, with emphasis on regulatory and rare functional variants involved in both aging and AD. This objective will be addressed using data collected in several longitudinal and cross-sectional human studies with genetic and phenotypic information on more than half a million individuals in total. Specific Aims: Aim 1. Identify new pleiotropic variants that influence both aging and AD traits, and evaluate their joint impacts on AD risk and survival. We will select such pleiotropic SNPs, using PheWas approach, and evaluate their collective impacts on AD and survival, using new methods of estimating joint effects of genetic interactions (Interaction Polygenic Risk Scores, IPRS). We will also specify pathways enriched in respective genes, and suggest mechanisms connecting them to AD. Aim 2. Investigate shared genetic mechanisms between physiological aging and AD, using candidate genes from relevant biological pathways, and suggest new targets for AD prevention. Our hypothesis is that genes, which products are connected in the same biological pathway/process relevant to both aging and AD, will work in concert and jointly significantly influence AD traits, especially in people with signs of accelerated physical aging. Based on current literature, we will select sets of candidate genes representing pathways that were linked to aging, and also relevant to AD (e.g., mitochondrial biogenesis declines with aging, and also (exacerbated) in AD), and regulatory elements such as miRNAs that influence translation of respective genes and protein levels. Then we will evaluate joint effects (additive, GxG, IPRS) of these genes on aging and AD traits, including in subsamples of individuals with signs of accelerated aging, and select candidate genetic targets that will be further validated in Aim 3. Aim 3. Preclinical validation of candidate genetic targets selected in Aims 1, 2, using biomarkers of AD pathology, and further exploration of mechanisms of observed associations. We will estimate effects of the selected variants on hippocampal volume, CSF and metabolic (FDG) biomarkers, and on cognitive scores, considering other covariates. We will also further explore causal relationships between genetic factors selected in Aims 1 and 2, and phenotypes of aging and AD, using Mendelian Randomization and related approaches. Results of this project will significantly